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Using the following methods forecast for all possible periods. Using the following methods forecast for all possible periods. Show the graph of actual and forecast

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Using the following methods forecast for all possible periods. Using the following methods forecast for all possible periods. Show the graph of actual and forecast

Moving average (you need to find the best value for n) Can you help me choose and explain the best value for n, explain how to choose this value ), please? Can you provide me the excel files to help me clear more?

Linear trend (trend projection)

Linear regression ( sorry can make the forecast)???

which one is the best method ( briefly explain) for the bank strategic plan to forecast the number of new accounts. Please help me explain and give the evidences. ( You can help me give some pros and cons of 3 aboved methods, after that explain how to choose the best method, what is the best approach in this case?

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Bank Account Forecast A well-known commercial bank in Australia is interested in estimating the number of new bank accounts opened by customers each year. The number of new accounts opened in this bank has increased slowly over years even during the global nancial crisis (20082009). Top management strongly believes that they need a long-term strategic plan for the bank which is a 5-year forecast for the number of new accounts opened. To achieve this aim, the bank operations manager examined past account data and also extracted the employment rate over 30 years (1991-2020). The resulting data are shown in below table: No of new Employment No of new Employment Year Rate % Year Rate % 1991 3.136 90.42 2006 6.00? 95.22 1992 3.309 89.2? 200? 5.826 95.62 1993 3.803 89.13 2008 8.266 95.?? 1994 6.80? 90.28 2009 ?.128 94.44 1995 2.386 91.53 2010 9.6?0 94.?9 1996 4.643 91.49 2011 11.419 94.92 199? 2.911 91.64 2012 11.335 94.?8 1998 2.553 92.32 2013 9.358 94.34 1999 4.422 93.13 2014 10.418 93.92 2000 3.613 93.?2 2015 10.459 93.95 2001 3.948 93.26 2016 ?.328 94.29 2002 3.34? 93.63 201? 9.004 94.41 2003 3.90? 94.0? 2018 8.559 94.?0 2004 4.0?1 94.60 2019 8.4?6 94.84 2005 6.666 94.9? 2020 8.635 93.39I

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